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Raw output: clm.c

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 0002: # cython: c_string_encoding=utf8
 0003: 
+0004: import ctypes
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+0005: from functools import singledispatch, partial
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+0006: import math
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+0007: import random
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+0008: import subprocess
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+0009: import tempfile
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+0010: import time
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+0011: import types
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 0012: import cython
 0013: from cython.cimports.cpython.mem import PyMem_Malloc, PyMem_Realloc, PyMem_Free
 0014: from cython cimport view
+0015: import numpy as np
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 0016: cimport numpy as np
+0017: import numpy.typing as npt
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 0018: cimport pysndlib.cclm as cclm
 0019: cimport pysndlib.csndlib as csndlib
+0020: from pysndlib.sndlib import Sample, Header
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 0021: 
+0022: np.import_array()
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 0023: 
 0024: 
 0025: # --------------- clm enums ---------------- #
+0026: cpdef enum Interp:
enum __pyx_t_8pysndlib_3clm_Interp {
  __pyx_e_8pysndlib_3clm_NONE,
  __pyx_e_8pysndlib_3clm_LINEAR,
  __pyx_e_8pysndlib_3clm_SINUSOIDAL,
  __pyx_e_8pysndlib_3clm_ALL_PASS,
  __pyx_e_8pysndlib_3clm_LAGRANGE,
  __pyx_e_8pysndlib_3clm_BEZIER,
  __pyx_e_8pysndlib_3clm_HERMITE
};
 0027:     """
 0028:     various interpolation types
 0029:     """
 0030:     NONE, LINEAR,SINUSOIDAL, ALL_PASS, LAGRANGE, BEZIER, HERMITE
 0031: 
+0032: cpdef enum Window:
enum __pyx_t_8pysndlib_3clm_Window {
  __pyx_e_8pysndlib_3clm_RECTANGULAR,
  __pyx_e_8pysndlib_3clm_HANN,
  __pyx_e_8pysndlib_3clm_WELCH,
  __pyx_e_8pysndlib_3clm_PARZEN,
  __pyx_e_8pysndlib_3clm_BARTLETT,
  __pyx_e_8pysndlib_3clm_HAMMING,
  __pyx_e_8pysndlib_3clm_BLACKMAN2,
  __pyx_e_8pysndlib_3clm_BLACKMAN3,
  __pyx_e_8pysndlib_3clm_BLACKMAN4,
  __pyx_e_8pysndlib_3clm_EXPONENTIAL,
  __pyx_e_8pysndlib_3clm_RIEMANN,
  __pyx_e_8pysndlib_3clm_KAISER,
  __pyx_e_8pysndlib_3clm_CAUCHY,
  __pyx_e_8pysndlib_3clm_POISSON,
  __pyx_e_8pysndlib_3clm_GAUSSIAN,
  __pyx_e_8pysndlib_3clm_TUKEY,
  __pyx_e_8pysndlib_3clm_DOLPH_CHEBYSHEV,
  __pyx_e_8pysndlib_3clm_HANN_POISSON,
  __pyx_e_8pysndlib_3clm_CONNES,
  __pyx_e_8pysndlib_3clm_SAMARAKI,
  __pyx_e_8pysndlib_3clm_ULTRASPHERICAL,
  __pyx_e_8pysndlib_3clm_BARTLETT_HANN,
  __pyx_e_8pysndlib_3clm_BOHMAN,
  __pyx_e_8pysndlib_3clm_FLAT_TOP,
  __pyx_e_8pysndlib_3clm_BLACKMAN5,
  __pyx_e_8pysndlib_3clm_BLACKMAN6,
  __pyx_e_8pysndlib_3clm_BLACKMAN7,
  __pyx_e_8pysndlib_3clm_BLACKMAN8,
  __pyx_e_8pysndlib_3clm_BLACKMAN9,
  __pyx_e_8pysndlib_3clm_BLACKMAN10,
  __pyx_e_8pysndlib_3clm_RV2,
  __pyx_e_8pysndlib_3clm_RV3,
  __pyx_e_8pysndlib_3clm_RV4,
  __pyx_e_8pysndlib_3clm_MLT_SINE,
  __pyx_e_8pysndlib_3clm_PAPOULIS,
  __pyx_e_8pysndlib_3clm_DPSS,
  __pyx_e_8pysndlib_3clm_SINC
};
 0033:     """
 0034:     many useful windows
 0035:     """
 0036:     RECTANGULAR, HANN, WELCH, PARZEN, BARTLETT, HAMMING, BLACKMAN2, BLACKMAN3, BLACKMAN4, EXPONENTIAL, RIEMANN, KAISER, CAUCHY, POISSON, GAUSSIAN, TUKEY, DOLPH_CHEBYSHEV, HANN_POISSON, CONNES, SAMARAKI, ULTRASPHERICAL, BARTLETT_HANN, BOHMAN, FLAT_TOP, BLACKMAN5, BLACKMAN6, BLACKMAN7, BLACKMAN8, BLACKMAN9, BLACKMAN10, RV2, RV3, RV4, MLT_SINE, PAPOULIS, DPSS, SINC,
 0037: 
+0038: cpdef enum Spectrum:
enum __pyx_t_8pysndlib_3clm_Spectrum {
  __pyx_e_8pysndlib_3clm_IN_DB,
  __pyx_e_8pysndlib_3clm_NORMALIZED,
  __pyx_e_8pysndlib_3clm_RAW
};
 0039:     """
 0040:     types of normalizations when using the spectrum function. The results are in dB if IN_DB, or linear and normalized to 1.0 NORMALIZED, or linear unnormalized RAW
 0041:     """
 0042:     IN_DB, NORMALIZED, RAW
 0043: 
+0044: cpdef enum Polynomial:
enum __pyx_t_8pysndlib_3clm_Polynomial {
  __pyx_e_8pysndlib_3clm_EITHER_KIND,
  __pyx_e_8pysndlib_3clm_FIRST_KIND,
  __pyx_e_8pysndlib_3clm_SECOND_KIND,
  __pyx_e_8pysndlib_3clm_BOTH_KINDS
};
 0045:     """
 0046:     used for polynomial based gens 
 0047:     """
 0048:     EITHER_KIND, FIRST_KIND, SECOND_KIND, BOTH_KINDS
 0049: 
 0050: 
 0051: 
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 0129: 
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 0133: 
 0134: 
 0135: # todo add mus_set_xcoeff and mus_set_ycoeff
 0136: 
 0137: # --------------- extension types ---------------- #
 0138: 
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 0167:     cdef np.ndarray _pv_freqs
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 0171:     cdef np.ndarray _pv_phase_increments
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 2054: 
 2055: # this is slow because of needing ctypes to define function at runtime
 2056: # but no other way to do it with cython without changing sndlib code
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  PyObject *outputfile;
  PyObject *sample_type;
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 4924:     """
 4925:     convolve-files handles a very common special case: convolve two files, then normalize the result to some maxamp.
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 4928:     :param file2: second file
 4929:     :param maxamp: amp to scale to
 4930:     :param outputfile: output file
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 4932:     :param header_type: header of sample type to use. defaults to clm.header_type
 4933:     :return: output file 
 4934:     :rtype: str
 4935:     """
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 4947: 
 4948: 
 4949: #########################################
 4950: # basic file reading/writing to/from nympy arrays
 4951: # note all of this assumes numpy dtype is np.double
 4952: # also assumes shape is (chan, length)
 4953: # a mono file that is 8000 samples long should
 4954: # be a numpy array created with something like
 4955: # arr = np.zeroes((1,8000), dtype=np.double)
 4956: # librosa follows this convention
 4957: #  todo : look at allowing something like np.zeroes((8000), dtype=np.double)
 4958: # to just be treated as mono sound buffer 
 4959: # the python soundfile library does this differently 
 4960: # and would use 
 4961: # arr = np.zeros((8000,1), dtype=np.double))
 4962: # this seems less intuitive to me 
 4963: # very issue to translate with simple np.transpose()
 4964: 
 4965: 
 4966: # cpdef sndinfo(filename):
 4967: #     """returns a dictionary of info about a sound file including write date (data), sample rate (srate),
 4968: #     channels (chans), length in samples (samples), length in second (length), comment (comment), and loop information (loopinfo)"""
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 4972: #     samples = csndlib.mus_sound_samples(filename)
 4973: #     comment = csndlib.mus_sound_comment(filename) 
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 4975: # 
 4976: #     header_type = header(mus_sound_header_type(filename))
 4977: #     sample_type = sample(mus_sound_sample_type(filename))
 4978: #     
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 4981: #         loop_modes = [loop_info[6], loop_info[7]]
 4982: #         loop_starts = [loop_info[0], loop_info[2]]
 4983: #         loop_ends = [loop_info[1], loop_info[3]]
 4984: #         base_note = loop_info[4]
 4985: #         base_detune = loop_info[5]
 4986: #     
 4987: #         loop_info = {'sustain_start' : loop_starts[0], 'sustain_end' : loop_ends[0], 
 4988: #                     'release_start' : loop_starts[2], 'release_end' : loop_ends[1],
 4989: #                     'base_note' : base_note, 'base_detune' : base_detune, 
 4990: #                     'sustain_mode' : loop_modes[0], 'release_mode' : loop_modes[1]}
 4991: #     
 4992: #     info = {'date' : time.localtime(date), 'srate' : srate, 'chans' : chans, 'samples' : samples,
 4993: #             'comment' : comment, 'length' : length, 'header_type' : header_type, 'sample_type' : sample_type,
 4994: #             'loop_info' : loop_info}
 4995: #     return info
 4996: 
 4997: # def sound_loop_info(filename):
 4998: #     """returns a dictionary of info about a sound file including write date (data), sample rate (srate),
 4999: #     channels (chans), length in samples (samples), length in second (length), comment (comment), and loop information (loopinfo)"""
 5000: #     
 5001: #     loop_info = sndlib.mus_sound_loop_info(filename)
 5002: #     if loop_info:
 5003: #         loop_modes = [loop_info[6], loop_info[7]]
 5004: #         loop_starts = [loop_info[0], loop_info[2]]
 5005: #         loop_ends = [loop_info[1], loop_info[3]]
 5006: #         base_note = loop_info[4]
 5007: #         base_detune = loop_info[5]
 5008: #     
 5009: #         loop_info = {'sustain_start' : loop_starts[0], 'sustain_end' : loop_ends[0], 
 5010: #                     'release_start' : loop_starts[2], 'release_end' : loop_ends[1],
 5011: #                     'base_note' : base_note, 'base_detune' : base_detune, 
 5012: #                     'sustain_mode' : loop_modes[0], 'release_mode' : loop_modes[1]}
 5013: #     return info
 5014: #     
 5015: # cpdef np.ndarray file2array(filename: str, channel: Optional[int]=0, beg: Optional[int]=None, dur: Optional[int]=None):
 5016: #     """
 5017: #     return an ndarray with samples from file
 5018: #     """
 5019: #     length = dur or csndlib.mus_sound_framples(filename)
 5020: #     chans = csndlib.mus_sound_chans(filename)
 5021: #     srate = csndlib.mus_sound_srate(filename)
 5022: #     bg = beg or 0
 5023: #     out = np.zeros(length, dtype=np.double)
 5024: #     
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 5026: #     out_view = out
 5027: # 
 5028: #     csndlib.mus_file_to_array(filename,channel, bg, length, &out_view[0])
 5029: #     return out
 5030: #     
 5031: # def channel2array(filename: str, channel: Optional[int]=0, beg: Optional[int]=None, dur: Optional[int]=None): 
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 5033: #     srate = mus_sound_srate(filename)
 5034: #     bg = beg or 0
 5035: #     out = np.zeros((1, length), dtype=np.double)
 5036: #     mus_file_to_array(filename,channel, bg, length, out[0].ctypes.data_as(ctypes.pointer(ctypes.c_double)))
 5037: #     return out
 5038: # 
 5039: # def calc_length(start, dur):
 5040: #     st = seconds2samples(start)
 5041: #     nd = seconds2samples(start+dur)
 5042: #     return st, nd
 5043: # 
 5044: # def convert_frequency(gen):
 5045: #     gen.frequency = hz2radians(gen.frequency)
 5046: #     return gen
 5047: # 
 5048: # # todo: maybe add an exception that have to use keyword args
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